#!/usr/bin/env python3
"""
WPS .dbt 文件迁移到飞书多维表格
"""

import pandas as pd
import requests
import json
import re
from datetime import datetime, timedelta
from typing import List, Dict, Any, Optional

# ========== 配置 ==========
ZHIYUN_APP_ID = "cli_a9f29dca82b9dbef"
ZHIYUN_APP_SECRET = "sDfhjG7QT1S4gfHiMVYSygmPQPN1R2Ho"
BASE_URL = "https://open.feishu.cn/open-apis"

# 源文件
SOURCE_FILE = "/Users/donglinlai/Downloads/酷采团购系统优化进度表.dbt.xlsx"


class FeishuBitable:
    """飞书多维表格操作工具类"""

    def __init__(self):
        self._token = None
        self._token_expires = None

    @property
    def token(self) -> str:
        if self._token and self._token_expires and datetime.now() < self._token_expires:
            return self._token

        url = f"{BASE_URL}/auth/v3/tenant_access_token/internal"
        response = requests.post(url, json={
            "app_id": ZHIYUN_APP_ID,
            "app_secret": ZHIYUN_APP_SECRET
        })
        data = response.json()

        if data.get("code") != 0:
            raise Exception(f"获取 token 失败: {data}")

        self._token = data["tenant_access_token"]
        self._token_expires = datetime.now() + timedelta(seconds=data.get("expire", 7200) - 60)
        return self._token

    @property
    def headers(self):
        return {
            "Authorization": f"Bearer {self.token}",
            "Content-Type": "application/json"
        }

    def create_bitable(self, name: str) -> Dict:
        """创建多维表格"""
        url = f"{BASE_URL}/bitable/v1/apps"
        response = requests.post(url, headers=self.headers, json={"name": name})
        data = response.json()

        if data.get("code") != 0:
            raise Exception(f"创建多维表格失败: {data}")

        return data["data"]["app"]

    def create_table(self, app_token: str, name: str, fields: List[Dict]) -> Dict:
        """创建数据表"""
        url = f"{BASE_URL}/bitable/v1/apps/{app_token}/tables"
        payload = {
            "table": {
                "name": name,
                "default_view_name": "默认视图",
                "fields": fields
            }
        }
        response = requests.post(url, headers=self.headers, json=payload)
        data = response.json()

        if data.get("code") != 0:
            raise Exception(f"创建数据表失败: {data}")

        return data["data"]

    def batch_create_records(self, app_token: str, table_id: str,
                             records: List[Dict], batch_size: int = 100) -> int:
        """批量创建记录"""
        url = f"{BASE_URL}/bitable/v1/apps/{app_token}/tables/{table_id}/records/batch_create"
        total_created = 0

        for i in range(0, len(records), batch_size):
            batch = records[i:i+batch_size]
            payload = {"records": [{"fields": r} for r in batch]}

            response = requests.post(url, headers=self.headers, json=payload)
            data = response.json()

            if data.get("code") != 0:
                print(f"    [WARN] 批次 {i//batch_size + 1} 部分失败: {data.get('msg', '')}")
                # 尝试逐条插入
                for record in batch:
                    try:
                        single_url = f"{BASE_URL}/bitable/v1/apps/{app_token}/tables/{table_id}/records"
                        single_resp = requests.post(single_url, headers=self.headers, json={"fields": record})
                        if single_resp.json().get("code") == 0:
                            total_created += 1
                    except:
                        pass
            else:
                total_created += len(data["data"]["records"])

        return total_created


def analyze_column_type(series: pd.Series, col_name: str) -> Dict:
    """分析列的数据类型，返回飞书字段定义"""
    col_lower = col_name.lower()

    # 根据列名判断类型
    if any(kw in col_lower for kw in ['日期', '时间', 'date', 'time', '提出时间', '发版日期', '更新时间']):
        return {"field_name": col_name, "type": 5, "property": {"date_formatter": "yyyy/MM/dd"}}

    if any(kw in col_lower for kw in ['图片', '附件', '截图', 'image', 'file', 'attachment']):
        return {"field_name": col_name, "type": 1}  # 作为文本处理

    if any(kw in col_lower for kw in ['优先级', '状态', '类型', '分类', '终端', '严重程度']):
        # 提取唯一值作为选项
        unique_vals = series.dropna().astype(str).unique()
        unique_vals = [v for v in unique_vals if v and v != 'nan' and len(v) < 50][:20]
        if len(unique_vals) > 0 and len(unique_vals) <= 20:
            return {
                "field_name": col_name,
                "type": 3,  # 单选
                "property": {
                    "options": [{"name": str(v)} for v in unique_vals]
                }
            }

    if any(kw in col_lower for kw in ['进度', '百分比', '%']):
        return {"field_name": col_name, "type": 2}  # 数字

    # 检查是否为数字列
    try:
        numeric_vals = pd.to_numeric(series.dropna(), errors='coerce')
        if numeric_vals.notna().sum() / max(len(series.dropna()), 1) > 0.8:
            return {"field_name": col_name, "type": 2}  # 数字
    except:
        pass

    # 默认为文本
    return {"field_name": col_name, "type": 1}


def clean_value(val: Any, field_type: int) -> Any:
    """清理和转换值"""
    if pd.isna(val) or val is None:
        return None

    if field_type == 5:  # 日期
        try:
            if isinstance(val, (datetime, pd.Timestamp)):
                return int(val.timestamp() * 1000)
            elif isinstance(val, str):
                dt = pd.to_datetime(val)
                return int(dt.timestamp() * 1000)
        except:
            return None

    if field_type == 2:  # 数字
        try:
            return float(val)
        except:
            return None

    if field_type == 3:  # 单选
        val_str = str(val).strip()
        if val_str and val_str != 'nan':
            return val_str
        return None

    # 文本类型
    val_str = str(val).strip()
    if val_str == 'nan' or not val_str:
        return None

    # 限制文本长度
    if len(val_str) > 10000:
        val_str = val_str[:10000] + "..."

    return val_str


def migrate_sheet(bitable: FeishuBitable, app_token: str,
                  df: pd.DataFrame, sheet_name: str) -> str:
    """迁移单个 Sheet 到数据表"""
    print(f"\n{'='*50}")
    print(f"迁移 Sheet: 【{sheet_name}】")
    print(f"{'='*50}")

    # 清理列名
    df.columns = [str(c).strip() for c in df.columns]

    # 去除完全空的行
    df = df.dropna(how='all')

    print(f"  数据: {len(df)} 行, {len(df.columns)} 列")

    # 分析字段类型
    fields = []
    field_types = {}
    for col in df.columns:
        if not col or col.startswith('Unnamed'):
            continue
        field_def = analyze_column_type(df[col], col)
        fields.append(field_def)
        field_types[col] = field_def["type"]

    print(f"  字段: {len(fields)} 个")

    # 创建数据表
    table_info = bitable.create_table(app_token, sheet_name, fields)
    table_id = table_info["table_id"]
    print(f"  [OK] 数据表创建成功: {table_id}")

    # 准备记录数据
    records = []
    for _, row in df.iterrows():
        record = {}
        for col in df.columns:
            if not col or col.startswith('Unnamed'):
                continue
            val = clean_value(row[col], field_types.get(col, 1))
            if val is not None:
                record[col] = val
        if record:  # 只添加非空记录
            records.append(record)

    print(f"  准备导入 {len(records)} 条记录...")

    # 批量创建记录
    if records:
        created = bitable.batch_create_records(app_token, table_id, records)
        print(f"  [OK] 成功导入 {created}/{len(records)} 条记录")
    else:
        print(f"  [INFO] 无有效数据")

    return table_id


def main():
    print("\n" + "#" * 60)
    print("#  WPS 文件迁移到飞书多维表格")
    print("#" * 60)

    bitable = FeishuBitable()

    # Step 1: 读取源文件
    print("\n" + "=" * 50)
    print("Step 1: 读取源文件")
    print("=" * 50)

    xlsx = pd.ExcelFile(SOURCE_FILE)
    print(f"  文件: {SOURCE_FILE}")
    print(f"  Sheet 数量: {len(xlsx.sheet_names)}")

    # Step 2: 创建多维表格
    print("\n" + "=" * 50)
    print("Step 2: 创建飞书多维表格")
    print("=" * 50)

    timestamp = datetime.now().strftime("%Y%m%d_%H%M")
    bitable_name = f"酷采团购系统优化进度表 (迁移 {timestamp})"

    app_info = bitable.create_bitable(bitable_name)
    app_token = app_info["app_token"]
    print(f"  [OK] 多维表格创建成功")
    print(f"       名称: {bitable_name}")
    print(f"       app_token: {app_token}")

    # Step 3: 迁移每个 Sheet
    print("\n" + "=" * 50)
    print("Step 3: 迁移数据表")
    print("=" * 50)

    table_ids = {}
    for sheet_name in xlsx.sheet_names:
        df = pd.read_excel(xlsx, sheet_name=sheet_name)
        table_id = migrate_sheet(bitable, app_token, df, sheet_name)
        table_ids[sheet_name] = table_id

    # 完成
    print("\n" + "=" * 60)
    print("迁移完成!")
    print("=" * 60)
    print(f"\n多维表格信息:")
    print(f"  名称: {bitable_name}")
    print(f"  app_token: {app_token}")
    print(f"\n数据表:")
    for name, tid in table_ids.items():
        print(f"  - {name}: {tid}")
    print(f"\n访问地址:")
    print(f"  https://zhiyuncai.feishu.cn/base/{app_token}")
    print()

    return app_token, table_ids


if __name__ == "__main__":
    main()